preProcess: Compute a weighted sample from initial observations
In logcondens: Estimate a Log-Concave Probability Density from Iid Observations

preProcess

R Documentation

Compute a weighted sample from initial observations

Generates weights from initial sample.

preProcess(x, xgrid = NULL)

`x`	Vector of independent and identically distributed numbers, not necessarily unique.
`xgrid`	Parameter that governs the generation of weights: If `xgrid = NULL` a new sample of unique observations is generated with corresponding vector of weights. If `xgrid` is a positive number, observations are binned in a grid with grid length `xgrid`. Finally, an entire vector specifying a user-defined grid can be supplied.

`x`	Vector of unique and sorted observations deduced from the input `x` according to the specification given by `xgrid`.
`w`	Vector of corresponding weights, normalized to sum to one.
`sig`	Standard deviation of the inputed observations. This quantity is needed when computing the smoothed log-concave density estimator via `evaluateLogConDens`.
`n`	Number of initial observations.